hindsight-local
Persistent memory storage for developer preferences and task learnings.
Install
mkdir -p .claude/skills/hindsight-local && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/3361" && unzip -o skill.zip -d .claude/skills/hindsight-local && rm skill.zipInstalls to .claude/skills/hindsight-local
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Store user preferences, learnings from tasks, and procedure outcomes. Use to remember what works and recall context before new tasks. (user)Key capabilities
- →Captures session learnings as structured facts
- →Links causal relationships between development events
- →Generates embeddings for semantic retrieval
- →Maintains local persistent state across sessions
How it works
Processes text input through an LLM to extract relationships, then embeds them for semantic storage in a local daemon.
Inputs & outputs
When to use hindsight-local
- →Saving project configuration preferences
- →Storing key takeaways from a debugging session
- →Recalling past procedure outcomes
About this skill
Hindsight Memory Skill (Local)
You have persistent memory via the hindsight-embed CLI. Proactively store learnings and recall context to provide better assistance.
Setup Check (First-Time Only)
Before using memory commands, verify Hindsight is configured:
uvx hindsight-embed daemon status
If this fails or shows "not configured", run the interactive setup:
uvx hindsight-embed configure
This will prompt for an LLM provider and API key. After setup, the commands below will work.
How Hindsight Works
When you call retain, Hindsight does not store the string as-is. The server runs an internal pipeline that:
- Extracts structured facts from the content using an LLM
- Identifies entities (people, tools, concepts) and links related facts
- Builds temporal and causal relationships between facts
- Generates embeddings for semantic search
This means you should pass rich, full-context content — the server is better at extracting what matters than a pre-summarized string. Your job is to decide when to store, not what to extract.
Commands
Store a memory
Use memory retain to store what you learn. Pass the full context — raw observations, session notes, conversation excerpts, or detailed descriptions:
uvx hindsight-embed memory retain default "User is working on a TypeScript project. They enabled strict mode and prefer explicit type annotations over inference."
uvx hindsight-embed memory retain default "Ran the test suite with NODE_ENV=test. Tests pass. Without NODE_ENV=test, the suite fails with a missing config error." --context procedures
uvx hindsight-embed memory retain default "Build failed on Node 18 with error 'ERR_UNSUPPORTED_ESM_URL_SCHEME'. Switched to Node 20 and build succeeded." --context learnings
You can also pass a raw conversation transcript with timestamps:
uvx hindsight-embed memory retain default "[2026-03-16T10:12:03] User: The auth tests keep failing on CI but pass locally. Any idea?
[2026-03-16T10:12:45] Assistant: Let me check the CI logs. Looks like the tests are running without the TEST_DATABASE_URL env var set — they fall back to the production DB URL and hit a connection timeout.
[2026-03-16T10:13:20] User: Ah right, I never added that to the CI secrets. Adding it now.
[2026-03-16T10:15:02] User: That fixed it. All green now." --context learnings
Recall memories
Use memory recall BEFORE starting tasks to get relevant context:
uvx hindsight-embed memory recall default "user preferences for this project"
uvx hindsight-embed memory recall default "what issues have we encountered before"
Reflect on memories
Use memory reflect to synthesize context:
uvx hindsight-embed memory reflect default "How should I approach this task based on past experience?"
IMPORTANT: When to Store Memories
Always store after you learn something valuable:
User Preferences
- Coding style (indentation, naming conventions, language preferences)
- Tool preferences (editors, linters, formatters)
- Communication preferences
- Project conventions
Procedure Outcomes
- Steps that successfully completed a task
- Commands that worked (or failed) and why
- Workarounds discovered
- Configuration that resolved issues
Learnings from Tasks
- Bugs encountered and their solutions
- Performance optimizations that worked
- Architecture decisions and rationale
- Dependencies or version requirements
IMPORTANT: When to Recall Memories
Always recall before:
- Starting any non-trivial task
- Making decisions about implementation
- Suggesting tools, libraries, or approaches
- Writing code in a new area of the project
Best Practices
- Store immediately: When you discover something, store it right away
- Pass rich context: Include full observations, not pre-summarized strings — the server extracts facts automatically
- Include outcomes: Store what happened AND why, including failures and workarounds
- Recall first: Always check for relevant context before starting work
- Use
--contextfor metadata: The--contextflag labels the type of memory (e.g.,procedures,learnings,preferences), not a replacement for full content
When not to use it
- →Scenarios requiring absolute data privacy (if storage is unencrypted)
- →Temporary tasks that do not benefit from historical recall
Prerequisites
Limitations
- →Dependent on quality of input context
- →Requires initial configuration for each machine
How it compares
Provides a persistent, searchable brain that grows based on the user's specific development history.
Compared to similar skills
hindsight-local side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| hindsight-local (this skill) | 1 | 5mo | Review | Beginner |
| notion-knowledge-capture | 10 | 9mo | No flags | Intermediate |
| apple-reminders | 25 | 2mo | Review | Beginner |
| memory-keeper-proactive-context-maintenance | 6 | 9mo | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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